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Machine learning in preclinical drug discovery
Drug-discovery and drug-development endeavors are laborious, costly and time consuming. These programs can take upward of 12 years and cost US $2.5...
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High Throughput Screening in Drug Discovery: Problems and Solutions
AbstractWorld-wide introduction of high throughput screening (HTS) methods in drug discovery research did not result in the increased number of novel...
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Biostatistical Investigation Using Docking Mechanism and Its Database to Investigate Drug Design, Drug Discovery, Drug Metabolism and Prediction Via Drug–Drug Interactions
Molecular docking is an important tool for structure-based drug design and is being widely used to study molecular interactions with proteins at...
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Molecular chameleons in drug discovery
Molecular chameleons possess a flexibility that allows them to dynamically shield or expose polar functionalities in response to the properties of...
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Databases for Drug Discovery and Development
Computational drug design and discovery have taken center stage attention during the time of COVID-19. The science community acknowledges the...
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Benchmarking compound activity prediction for real-world drug discovery applications
Identifying active compounds for target proteins is fundamental in early drug discovery. Recently, data-driven computational methods have...
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Decrypting orphan GPCR drug discovery via multitask learning
The drug discovery of G protein-coupled receptors (GPCRs) superfamily using computational models is often limited by the availability of protein...
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Perspectives on Anti-Tuberculosis Drug Discovery
Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis and is the second leading reason of death worldwide from infectious diseases...
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A compact review of progress and prospects of deep learning in drug discovery
BackgroundDrug discovery processes, such as new drug development, drug synergy, and drug repurposing, consume significant yearly resources....
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Target identification of small molecules: an overview of the current applications in drug discovery
Target identification is an essential part of the drug discovery and development process, and its efficacy plays a crucial role in the success of any...
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Consensus holistic virtual screening for drug discovery: a novel machine learning model approach
In drug discovery, virtual screening is crucial for identifying potential hit compounds. This study aims to present a novel pipeline that employs...
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Pocket Crafter: a 3D generative modeling based workflow for the rapid generation of hit molecules in drug discovery
We present a user-friendly molecular generative pipeline called Pocket Crafter, specifically designed to facilitate hit finding activity in the drug...
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Improvement of multi-task learning by data enrichment: application for drug discovery
Multi-task learning in deep neural networks has become a topic of growing importance in many research fields, including drug discovery. However,...
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Augmented ant colony algorithm for virtual drug discovery
Docking is a fundamental problem in computational biology and drug discovery that seeks to predict a ligand���s binding mode and affinity to a target...
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Current Trends in Computational Modeling for Drug Discovery
This contributed volume offers a comprehensive discussion on how to design and discover pharmaceuticals using computational modeling techniques. The...
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Antimalarial Drug Discovery and Development: From Bench to Bedside
Malaria is a mosquito-borne disease that wreaks devastation all over the world. Plasmodium, the disease’s causative agent, is spread via female...
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Natural Product Experiments in Drug Discovery
This detailed volume explores a wide range of evidence-based complementary medicine and various bio-analytical techniques used to define botanical...
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The slow but steady rise of binding free energy calculations in drug discovery
Binding free energy calculations are increasingly used in drug discovery research to predict protein-ligand binding affinities and to prioritize...
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Deep learning tools for advancing drug discovery and development
A few decades ago, drug discovery and development were limited to a bunch of medicinal chemists working in a lab with enormous amount of testing,...
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Hit discovery of potential CDK8 inhibitors and analysis of amino acid mutations for cancer therapy through computer-aided drug discovery
Cyclin-dependent kinase 8 (CDK8) has emerged as a promising target for inhibiting cancer cell function, intensifying efforts towards the development...
